IE interfaces (산업공학)

Korean Institute of Industrial Engineers (대한산업공학회)
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Selection of Important Variables in the Classification Model for Successful Flight Training

조종사 비행훈련 성패예측모형 구축을 위한 중요변수 선정

  • Lee, Sang-Heon (Department of Operations Research, Korea National Defense University) ;
  • Lee, Sun-Doo (Department of Operations Research, Korea National Defense University)
  • 이상헌 (국방대학교 운영분석학과) ;
  • 이선두 (국방대학교 운영분석학과)
  • Received : 20060300
  • Accepted : 20061200
  • Published : 2007.03.31
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Abstract

The main purpose of this paper is cost reduction in absurd pilot positive expense and human accident prevention which is caused by in the pilot selection process. We use classification models such as logistic regression, decision tree, and neural network based on aptitude test results of 505 ROK Air Force applicants in 2001~2004. First, we determine the reliability and propriety against the aptitude test system which has been improved. Based on this conference flight simulator test item was compared to the new aptitude test item in order to make additional yes or no decision from different models in terms of classification accuracy, ROC and Response Threshold side. Decision tree was selected as the most efficient for each sequential flight training result and the last flight training results predict excellent. Therefore, we propose that the standard of pilot selection be adopted by the decision tree and it presents in the aptitude test item which is new a conference flight simulator test.

Keywords

References

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